Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "9"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 9 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 31 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 9, Node N02:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460015 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.804457 -0.809231 3.656296 -0.860906 -0.519893 -0.040262 1.620092 -0.687308 0.5566 0.5813 0.3523 nan nan
2460014 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.211316 -0.605100 2.569130 -0.880691 2.562100 0.133599 2.589556 -0.595162 0.5311 0.5615 0.3522 nan nan
2460013 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.709900 -0.809281 3.644597 -0.948142 0.317859 -0.050410 2.520229 -0.728408 0.5508 0.5831 0.3610 nan nan
2460012 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.616938 -0.705137 3.492276 -1.079968 0.417618 0.208464 2.631817 -0.780206 0.5521 0.5828 0.3559 nan nan
2460011 digital_ok 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2460010 digital_ok 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2460009 digital_ok 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2460008 digital_ok 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2460007 digital_ok 100.00% 100.00% 100.00% 0.00% - - 236.913659 236.886601 inf inf 2557.266674 2613.707432 7000.303204 7409.513405 nan nan nan nan nan
2459999 digital_ok 0.00% 99.83% 99.67% 0.00% - - nan nan nan nan nan nan nan nan 0.1449 0.2410 0.1443 nan nan
2459998 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.106669 -0.391529 3.075204 -0.798087 0.179218 -0.065895 3.766346 -0.625513 0.5727 0.6110 0.3900 nan nan
2459997 digital_ok 100.00% 0.00% 0.00% 0.00% - - 1.221758 -0.659446 3.252037 -0.762271 -0.295155 -0.095827 5.396427 -0.763972 0.5857 0.6264 0.3920 nan nan
2459996 digital_ok 100.00% 0.00% 0.00% 0.00% - - 1.537785 -0.227383 4.477688 -0.698110 -0.451732 -0.008677 2.622076 -0.193927 0.5943 0.6305 0.4019 nan nan
2459995 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.522813 -0.442522 3.764908 -1.130939 0.904286 -0.277852 1.869945 -0.450627 0.5879 0.6268 0.3919 nan nan
2459994 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.055727 -0.343533 3.233152 -0.842271 0.990402 0.007929 1.054649 -0.750894 0.5817 0.6196 0.3894 nan nan
2459993 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.489970 -0.540804 2.812124 -1.021578 1.174292 -0.053958 2.062244 -0.054547 0.5733 0.6276 0.3975 nan nan
2459991 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.467563 -0.862811 3.068647 -1.002544 0.981004 -0.045500 2.212466 -0.422922 0.5873 0.6205 0.3950 nan nan
2459990 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.298958 -0.617676 2.968845 -1.070153 0.484622 -0.161348 2.479161 -0.780396 0.5859 0.6212 0.3938 nan nan
2459989 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.628649 -0.785512 2.613873 -0.719754 0.690671 -0.037074 1.246183 -0.831820 0.5823 0.6204 0.3965 nan nan
2459988 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.918159 -0.882125 3.052686 -1.229257 0.886974 -0.466354 1.242465 -0.657040 0.5832 0.6176 0.3860 nan nan
2459987 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.013386 -0.626555 3.012221 -0.950235 -0.472953 0.010095 1.327892 -0.790130 0.5890 0.6281 0.3864 nan nan
2459986 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.640484 -0.603012 3.286211 -1.206941 0.677077 -0.428379 3.140038 0.194318 0.6028 0.6429 0.3560 nan nan
2459985 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.208590 -0.695312 3.145253 -0.968340 -0.565810 -0.021929 3.553359 -0.778670 0.5880 0.6261 0.3963 nan nan
2459984 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.176601 -0.656724 3.373500 -0.998789 -0.951005 0.219908 1.250393 -0.700529 0.6044 0.6425 0.3731 nan nan
2459983 digital_ok 100.00% 0.00% 0.00% 0.00% - - 0.396500 -0.611497 3.064181 -1.114007 1.581595 -0.479747 4.318483 1.525289 0.6241 0.6617 0.3238 nan nan
2459982 digital_ok 0.00% 0.00% 0.00% 0.00% - - -0.638409 -1.131695 2.558729 -0.702327 0.670672 0.115949 2.332661 0.245390 0.6624 0.6742 0.3023 nan nan
2459981 digital_ok 100.00% 0.00% 0.00% 0.00% - - 0.285795 -0.646518 3.181342 -1.361929 5.975340 0.581450 1.725880 -0.418105 0.5890 0.6232 0.3908 nan nan
2459980 digital_ok 100.00% 0.00% 0.00% 0.00% - - 4.136662 -0.522528 7.853574 -0.387596 5.220914 -0.168905 3.974605 1.460651 0.5015 0.6571 0.3797 nan nan
2459979 digital_ok 100.00% 0.00% 0.00% 0.00% - - 4.566928 -0.651692 7.268616 -0.420275 4.743921 -0.010637 -0.299582 -0.638588 0.4320 0.6195 0.4490 nan nan
2459978 digital_ok 100.00% 0.00% 0.00% 0.00% - - 4.595654 -0.349990 7.910286 -0.482965 5.176173 -0.295605 -0.328583 -0.507138 0.4305 0.6150 0.4532 nan nan
2459977 digital_ok 100.00% 0.00% 0.00% 0.00% - - 4.682603 0.058611 7.738917 -0.386586 4.850663 -0.081115 -0.206767 -0.564102 0.3975 0.5792 0.4085 nan nan
2459976 digital_ok 100.00% 0.00% 0.00% 0.00% - - 4.663526 -0.302685 8.199134 -0.461533 5.643086 -0.226934 -0.177665 -0.669563 0.4408 0.6252 0.4512 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 9: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Temporal Discontinuties 2.589556 0.211316 -0.605100 2.569130 -0.880691 2.562100 0.133599 2.589556 -0.595162

Antenna 9: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.644597 0.709900 -0.809281 3.644597 -0.948142 0.317859 -0.050410 2.520229 -0.728408

Antenna 9: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.492276 0.616938 -0.705137 3.492276 -1.079968 0.417618 0.208464 2.631817 -0.780206

Antenna 9: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Shape nan nan nan inf inf nan nan nan nan

Antenna 9: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Shape nan nan nan inf inf nan nan nan nan

Antenna 9: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Shape nan nan nan inf inf nan nan nan nan

Antenna 9: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok nn Shape nan nan nan inf inf nan nan nan nan

Antenna 9: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power inf 236.913659 236.886601 inf inf 2557.266674 2613.707432 7000.303204 7409.513405

Antenna 9: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 9: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Temporal Discontinuties 3.766346 1.106669 -0.391529 3.075204 -0.798087 0.179218 -0.065895 3.766346 -0.625513

Antenna 9: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Temporal Discontinuties 5.396427 1.221758 -0.659446 3.252037 -0.762271 -0.295155 -0.095827 5.396427 -0.763972

Antenna 9: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 4.477688 1.537785 -0.227383 4.477688 -0.698110 -0.451732 -0.008677 2.622076 -0.193927

Antenna 9: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.764908 1.522813 -0.442522 3.764908 -1.130939 0.904286 -0.277852 1.869945 -0.450627

Antenna 9: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.233152 1.055727 -0.343533 3.233152 -0.842271 0.990402 0.007929 1.054649 -0.750894

Antenna 9: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 2.812124 1.489970 -0.540804 2.812124 -1.021578 1.174292 -0.053958 2.062244 -0.054547

Antenna 9: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.068647 1.467563 -0.862811 3.068647 -1.002544 0.981004 -0.045500 2.212466 -0.422922

Antenna 9: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 2.968845 -0.617676 1.298958 -1.070153 2.968845 -0.161348 0.484622 -0.780396 2.479161

Antenna 9: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 2.613873 -0.785512 0.628649 -0.719754 2.613873 -0.037074 0.690671 -0.831820 1.246183

Antenna 9: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.052686 -0.882125 0.918159 -1.229257 3.052686 -0.466354 0.886974 -0.657040 1.242465

Antenna 9: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.012221 1.013386 -0.626555 3.012221 -0.950235 -0.472953 0.010095 1.327892 -0.790130

Antenna 9: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.286211 -0.603012 1.640484 -1.206941 3.286211 -0.428379 0.677077 0.194318 3.140038

Antenna 9: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Temporal Discontinuties 3.553359 -0.695312 1.208590 -0.968340 3.145253 -0.021929 -0.565810 -0.778670 3.553359

Antenna 9: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 3.373500 1.176601 -0.656724 3.373500 -0.998789 -0.951005 0.219908 1.250393 -0.700529

Antenna 9: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Temporal Discontinuties 4.318483 0.396500 -0.611497 3.064181 -1.114007 1.581595 -0.479747 4.318483 1.525289

Antenna 9: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 2.558729 -0.638409 -1.131695 2.558729 -0.702327 0.670672 0.115949 2.332661 0.245390

Antenna 9: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Temporal Variability 5.975340 -0.646518 0.285795 -1.361929 3.181342 0.581450 5.975340 -0.418105 1.725880

Antenna 9: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 7.853574 -0.522528 4.136662 -0.387596 7.853574 -0.168905 5.220914 1.460651 3.974605

Antenna 9: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 7.268616 4.566928 -0.651692 7.268616 -0.420275 4.743921 -0.010637 -0.299582 -0.638588

Antenna 9: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 7.910286 -0.349990 4.595654 -0.482965 7.910286 -0.295605 5.176173 -0.507138 -0.328583

Antenna 9: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 7.738917 4.682603 0.058611 7.738917 -0.386586 4.850663 -0.081115 -0.206767 -0.564102

Antenna 9: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
9 N02 digital_ok ee Power 8.199134 -0.302685 4.663526 -0.461533 8.199134 -0.226934 5.643086 -0.669563 -0.177665
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